How Generative Artificial Intelligence Creates Value: A Function and Readiness Perspective in Small and Medium-Sized Enterprises

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Authors: Leandro Bitetti, Carmine Garzia, Emanuele Carpanzano
Cited by: 2
References: 53

Abstract

Generative artificial intelligence (GenAI) is increasingly portrayed as a transformative technology capable of simultaneously enhancing operational efficiency and enabling strategic growth. Yet small and medium-sized enterprises (SMEs) experience heterogeneous outcomes, suggesting that GenAI does not generate value uniformly across firms. This study develops and empirically informs a contingency framework explaining how distinct GenAI functions relate to differentiated strategic objectives and how technological, organizational, and environmental (TOE) readiness conditions shape this relationship. Using a three-round Delphi study with an interdisciplinary expert panel, including GenAI consultants, corporate managers, legal experts, academic researchers, and public-sector policymakers, we identify six core GenAI functional domains associated with efficiency-oriented and growth-oriented strategies. The findings suggest that operational automation and data intelligence are more strongly associated with efficiency objectives, whereas market intelligence, market testing, linguistic expansion, and idea generation are more closely related to growth objectives, although none is exclusively linked to a single strategic goal. Importantly, TOE readiness is found to play a key role in shaping the extent to which function-specific GenAI deployment translates into realized strategic value, with organizational readiness appearing more prominent than technological or environmental conditions. By shifting the focus from adoption to function-specific strategic alignment and readiness configurations, this study advances understanding of GenAI-enabled strategic value realization and heterogeneous transformation pathways in SMEs.

Fields of Study & Subjects

Big Data and Business Intelligence Delphi Technique in Research AI in Service Interactions

Publication details

Journal / source
Administrative Sciences
Publisher
MDPI AG
Volume
16
Issue
4
Pages
176–176
Publication date
3 April 2026
Language
EN